Title :
An automatic branch and stenoses detection in computed tomography angiography
Author :
Cetin, Suheyla ; Unal, Gozde ; Degertekin, Muzaffer
Author_Institution :
Comput. Sci., Sabanci Univ., Istanbul, Turkey
Abstract :
In this work, we present an automatic branch and stenoses detection method that is capable of detecting all types of plaques in Computed Tomography Angiography (CTA) modality. Our method is based on the vessel extraction algorithm we proposed in [1], and detects branches and stenoses in a very fast way. We demonstrate the performance of our branch detection method on 3 complex tubular structured synthetic datasets for quantitative validation. Additionally, we show the preliminary results of stenoses detection algorithm on 11 CTA volumes, which are qualitatively evaluated by a cardiologist expert.
Keywords :
computerised tomography; diagnostic radiography; diseases; medical image processing; automatic branch detection method; complex tubular structured synthetic datasets; computed tomography angiography; quantitative validation; stenoses detection method; vessel extraction algorithm; Algorithm design and analysis; Arteries; Computed tomography; Image segmentation; Noise; Tensile stress; Vectors; CTA; branch detection; coronary arteries; segmentation; stenosis detection; tubular structures; vessel trees;
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1857-1
DOI :
10.1109/ISBI.2012.6235615